Design and Evaluation of a Low-Power Sensor Device for Induced Rockfall Experiments

Rockfalls have over the last decades become a serious and frequent hazard, especially due to larger variations in precipitation and temperatures, destabilizing rocky slopes in mountainous regions.Hence, civil engineers are applying the latest simulation tools to perform risk assessments and plan mitigation strategies.These tools are based on various models with many parameters that should be calibrated and evaluated with real-world in-field measurement data.In this work, we present a rugged low-power multi-sensor node termed StoneNode, that has been designed to acquire and log accurate inertial sensor measurements during induced infield experiments with falling rocks.The node hosts low-power MEMS sensors with high dynamic ranges sampled up to 1 kHz, and provides a long battery life-time of up to 56 h, enabling long-lasting field studies with a duration of several working days.Exhaustive in-field experiments have been carried out with several differently shaped rocks on typical terrain in the Swiss alpine region.The experiments comprise more than 100 induced tests with several heavy impacts of >400 g.This paper gives a detailed summary of these results, including unprecedented insitu data of rock fall trajectories and post-experimental validation where we compare simulated rockfall deposition distributions and motion traces with in-field measurements after calibration of the simulation module.Our results and experience gained in-field confirm that the StoneNode is a reliable, easy-to-use device, which greatly facilitates the data acquisition process.Further, the results obtained with the calibrated simulation tool shows good quantitative and qualitative congruence with the experiments, further reaffirming our methodological approach.